Journal of the American Society of Echocardiography最新文献

Background: In healthy subjects, sex differences in right heart function have been detected for various echocardiographic parameters. The objective of this study was to investigate sex differences in echocardiographic European Society of Cardiology (ESC)/European Respiratory Society (ERS) risk stratification parameters and their impact on survival estimation in patients with pulmonary arterial hypertension (PAH).

Methods: In this retrospective, cross-sectional study with a mean follow-up time of 3.2 ± 2.65 years (median, 2.78 years), clinical parameters including right atrial (RA) area, right ventricular area, and tricuspid annular plane systolic excursion (TAPSE) divided by systolic pulmonary artery pressure (sPAP) were assessed. Thresholds of ESC/ERS risk stratification were compared using multivariable Cox regression analysis.

Results: Of 748 patients with PAH (mean age, 65 ± 15 years; 63% women), men had significantly larger right heart size than women (RA area 21.76 ± 7.64 vs 17.65 ± 6.82 cm², P < .001; right ventricular area 24.02 ± 7.15 cm² vs 18.41 ± 5.75 cm², P < .001). This difference was consistent throughout all World Health Organization functional classes and cardiac index risk groups, except for the RA area in the cardiac index high-risk group and World Health Organization functional class IV. On multivariable analysis, indexed values showed more pronounced differences for age-adjusted survival analysis compared with ESC/ERS risk stratification thresholds. TAPSE/sPAP showed no significant sex differences, which makes this parameter a robust prognostic predictor.

Conclusions: This is the first study focusing on sex differences in right heart size obtained by echocardiography in patients with PAH. For risk stratification indexing RA area to body surface area could be more reflective of body composition. In contrast, TAPSE/sPAP values were not sex dependent and were a robust prognostic factor in patients with PAH.

Background: When assessing right ventricular (RV) function by echocardiography, some discordance between the deformational indices is predicted on the basis of the influence of RV length. RV free wall longitudinal strain (RVFWS) is relatively independent of RV length, whereas tricuspid annular plane systolic excursion (TAPSE) reflects the strain-length product. Systolic annular velocity (s'; distance over time) is also likely to be influenced by length. The aim of this study was to test the hypothesis that indexing TAPSE and s' to RV length would lead to better congruency with RVFWS.

Methods: Two separate cohorts were identified from retrospective data: (1) subjects with normal cardiac function (n = 75) and (2) a cohort with high likelihood of potential RV dysfunction determined by the study indication of either pulmonary hypertension or pulmonary embolism (n = 50). RV functional indices of TAPSE, RV s', RVFWS, and fractional area change were verified and remeasured by an expert. Correlations and concordance maps between RVFWS and either TAPSE or RV s' were made with and without indexing the latter measurements to RV length. Predictive accuracy for detecting abnormal RVFWS were made using receiver operating characteristics analysis.

Results: In normal subjects, indexing either TAPSE or RV s' to RV length led to an improvement in the correlation coefficient (from 0.59 to 0.68 for TAPSE, from 0.41 to 0.58 for RV s') and the variance (F statistic from 64.9 to 105.3 for TAPSE from 24.7 to 63.9 for RV s') for correlations with RVFWS. In all subjects, categorical concordance with RVFWS was improved by indexing TAPSE and s' to RV length primarily because of correction of underperformance to detect abnormal RVFWS in subjects with long RV length and better discrimination as normal for subjects with short RV length. Indexing to RV length improved the C statistic for detecting abnormal RVFWS for both TAPSE (0.80 vs 0.87, P = .03) and RV s' (0.65 vs 0.77, P = .002).

Conclusions: Indexing TAPSE and RV s' to RV length improves concordance of these deformational measurements with RVFWS and their ability to classify those with RV dysfunction according to RVFWS. Indexing TAPSE and RV s' to length is particularly effective for interpreting paradoxical information such as low TAPSE and s' in normal patients with short RV length and those with increased RV length who have normal TAPSE and s' values but other evidence of RV dysfunction.

Exercise intolerance is a hallmark symptom in adults with tetralogy of Fallot (TOF). This may be attributed to impairments in right ventricular (RV) function, augmentation in RV load, and their effect on left ventricular (LV) hemodynamics. To elucidate these mechanisms, we examined oxygen uptake (VO₂) and cardiac hemodynamics in TOF and healthy controls at rest and during exercise. At peak exercise, VO₂ was lower in TOF. This was partially attributed to lower heart rate in conjunction with a blunted exercise-induced change in LV stroke volume from rest to compensate for the chronotropic incompetence. Additionally, at peak exercise, pulmonary-RV was higher in TOF. Additionally, at peak exercise, in TOF, pulmonary-RV coupling negatively correlated with VO₂ , changes in LV end-diastolic volume, and changes in LV SV from rest. These findings reveal the reliance of LV hemodynamics on the interplay between RV systolic load and function during exercise in TOF.

Background: Exposure to high altitude may unpredictably lead to acute mountain sickness (AMS). The purpose of this study was to identify the predictors of AMS at low altitude using exercise stress echocardiography (ESE).

Methods: A total of 40 healthy adults were enrolled and underwent comprehensive supine bicycle ESE at low altitude, including pulmonary vascular resistance (PVR), right ventricular area index at the end of diastole, B-lines, and inferior vena cava (IVC) diameter. All subjects ascended to 3,600 m within 24 hours. The risk factors for AMS were screened using least absolute shrinkage and selection operator regression analysis. A novel nomogram model was then established using multivariable logistic regression analysis, and a clinical impact curve was constructed.

Results: At the altitude of 3,600 m, 20 of 40 subjects had AMS (AMS group). On least absolute shrinkage and selection operator regression analyses, PVR, IVC, and B-lines at peak exercise were all independent factors influencing AMS. The nomogram built on the basis of these factors predicted AMS with sensitivity of 0.950 and specificity of 0.804, which outperformed the individual predictive C indexes of each indicator (nomogram: cutoff, 59.3; area under the curve [AUC], 0.90 [95% CI, 0.80-1.00]; PVR at peak exercise: cutoff, 1.55; AUC, 0.81 [95% CI, 0.70-0.91]; B-lines at peak exercise: cutoff, 1; AUC, 0.78 [95% CI, 0.69-0.92]; IVC at peak exercise: cutoff, 13.8; AUC, 0.74 [95% CI, 0.65-0.87]). The established model was validated by plotting the clinical decision curve analysis and clinical impact curve.

Conclusions: Supine bicycle ESE is a useful technique to identify subjects susceptible to AMS. This study established a nomogram to predict the development to AMS with high discrimination and accuracy.

Introduction: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.

Objectives: We aimed to investigate the accuracy of a machine learning (ML)-model based on initial transthoracic echocardiography (TTE) to predict in-hospital major adverse events (MAEs) in a broad spectrum of patients admitted to ICCU.

Methods: All consecutive patients hospitalized in ICCUs with a complete TTE performed within the first 24 hours of admission were included in this prospective multicenter study (39 centers). Sixteen TTE parameters were evaluated. The ML model involved automated feature selection by random survival forest and model building with an extreme gradient boosting (XGBoost) algorithm. The primary outcome was in-hospital MAEs defined as all-cause death, resuscitated cardiac arrest, or cardiogenic shock.

Results: Of 1,499 consecutive patients (63 ± 15 years, 70% male), MAEs occurred in 67 patients (4.5%). The 5 TTE parameters selected in the model were left ventricular outflow tract velocity-time integral, E/e' ratio, systolic pulmonary artery pressure, tricuspid annular plane systolic excursion, and left ventricular ejection fraction. Using the XGBoost, the ML model exhibited a higher area under the receiver operating curve compared with any existing scores (ML model, 0.83 vs logistic regression, 0.76, ACUTE-HF score:,0.66; thrombolysis in myocardial infarction score, 0.60; Global Registry of Acute Coronary Events score, 0.58, all P < .001). The ML model had an incremental prognostic value for predicting MAE over a traditional model including clinical and biological data (C index 0.80 vs 0.73, P = .012; chi-square 59.7 vs 32.4; P < .001).

Conclusion: The ML model based on initial TTE exhibited a higher prognostic value to predict in-hospital MAEs compared with existing scores or clinical and biological data in the ICCU.

Background: In the multiparametric framework for diagnosing atrial secondary tricuspid regurgitation (A-STR), an end-systolic (ES) right atrial (RA)-to-right ventricular (RV) volume or area ratio ≥1.5 supports the diagnosis of A-STR over the ventricular secondary tricuspid regurgitation phenotype (V-STR). However, this threshold value has never been tested.

Methods: A single-center study was conducted, prospectively enrolling consecutive patients with secondary tricuspid regurgitation who underwent two- and three-dimensional echocardiography.

Results: A total of 350 patients were enrolled (mean age, 75 ± 13 years; 65% women). Although patients with A-STR and V-STR presented similar degrees of secondary tricuspid regurgitation and comparable RA size, the ES RA/RV volume ratio was significantly larger in A-STR than in V-STR (1.75 [interquartile range, 1.35-2.45] vs 1.18 [interquartile range, 0.81-1.66], respectively; P < .001). On receiver operating characteristic analysis, the ES RA/RV volume ratio showed a significantly higher predictive power for A-STR (area under the curve [AUC], 0.73; 95% CI, 0.68-0.78) compared with RA maximum volume (AUC, 0.6; 95% CI, 0.54-0.66; P = .01), RA minimum volume (AUC, 0.59; 95% CI, 0.53-0.65; P = .007), and ratio of RA minimum volume to RV end-diastolic volume (AUC, 0.57; 95% CI, 0.51-0.63; P < .001). However, the predictive power of the ES RA/RV volume ratio (AUC, 0.73; 95% CI, 0.68-0.78) and the ES RA/RV area ratio (AUC, 0.76; 95% CI, 0.71-0.81) for the diagnosis of A-STR was similar (P = .58). The threshold value for ES RA/RV volume ratio that best distinguished between A-STR and V-STR was 1.40 (AUC, 0.68; 95% CI, 0.63-0.73), whereas for ES RA/RV area ratio, it was 1.6 (AUC, 0.64; 95% CI, 0.59-0.69). A multivariable model that included either ES RA/RV volume ratio or ES RA/RV area ratio, along with LV ejection fraction, RV ejection fraction, RV ES volume, and pulmonary artery systolic pressure, resulted in an AUC of 0.97 for differentiating between A-STR and V-STR.

Conclusions: ES RA/RV volume ratio ≥ 1.4 and ES RA/RV area ratio ≥ 1.6 support the diagnosis of A-STR over V-STR.